Title :
An On-line Probabilistic Paradigm for Optimal Disassembly Planning
Author :
Tang, Ying ; Renner, Peter
Author_Institution :
Electr. & Comput. Eng. Dept., Rowan Univ., Glassboro, NJ
Abstract :
Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem
Keywords :
assembly planning; belief networks; learning (artificial intelligence); optimised production technology; probability; uncertainty handling; Bayesian learning; material recovery; online probabilistic paradigm; optimal disassembly planning; product recovery; Assembly; Cost function; Decision making; Fuzzy systems; Kernel; Manufacturing; Predictive models; Recycling; Reverse logistics; Uncertainty; Bayesian learning; disassembly Petri net; optimal disassembly planning;
Conference_Titel :
Service Operations and Logistics, and Informatics, 2006. SOLI '06. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
1-4244-0317-0
Electronic_ISBN :
1-4244-0318-9
DOI :
10.1109/SOLI.2006.329087
